关于 Hacker News 的 LLM 研究正在减少。

关于 Hacker News 的 LLM 研究正在减少。
LLM research on Hacker News is drying up

原始链接: https://dylancastillo.co/til/llm-research-on-hacker-news-is-dying.html

最近对Hacker News (HN) BigQuery数据集的分析显示，arXiv论文在该平台上的分享数量有所下降。arXiv帖子曾在2019年左右达到高峰，这主要得益于深度学习研究（在点赞最多的论文中占41%），但近几个月其出现频率显著降低。目前（2023-2026年），大型语言模型 (LLM) 和人工智能占据主导地位，占HN上点赞最多的arXiv论文的59%。该分析还确定了来自2019年并持续具有影响力的“老”论文，包括关于MuZero、EfficientNet、XLNet、PyTorch以及Chollet的《关于智能的度量》等研究。展望未来，Claude预测了一些潜在的未来有影响力的论文，例如DeepSeek-R1、Generative Agents、BitNet、Differential Transformer，甚至是有争议的LK-99超导体预印本，突显了LLM推理、代理架构和高效计算的持续趋势。这项研究表明，HN的关注点正在从更广泛的深度学习领域转向更具体的LLM领域。

最近的 Hacker News 讨论指出，平台上分享的原创 LLM 研究似乎在减少。一篇声称分析研究趋势的文章，严重依赖于查询 Claude AI 模型（“我问了 Claude……”），却没有提供底层数据或方法论，因此受到了批评，被认为缺乏实质内容。评论者指出，Hacker News 不适合深入的论文讨论，更倾向于快速的观点而非详细的分析。他们还指出了一个更广泛的问题：能够进行细致对话的专家参与度有限，尤其是在商业实验室变得不透明，研究变得越来越渐进的情况下。关于寻找更好讨论论坛的建议包括：专门的 Reddit 子版块、Discord 社区（但如果没有激励措施则难以维护），以及直接联系论文作者——据报道，回复率出乎意料地高。最终，这场对话表明需要专门的空间来进行计算机科学研究的专注、知情的讨论。

I thought I was seeing fewer arXiv papers on the front page of Hacker News (HN) these days, and I wanted to check if that was real.

So I asked Claude to run a quick analysis: track the share of arXiv stories on HN over time. It queried the BigQuery HN dataset, bucketed the stories by month, and plotted the series:

Percentage of HN stories linking to arXiv

That confirmed my hunch. arXiv posts have been decreasing rapidly in the last few months. Interestingly, it also showed another peak around 2019, and I wanted to know what drove it.

I asked Claude to pull the top 100 papers by upvotes from 2019 and group them by topic. It was the deep learning peak. 41% of the top 100 were about deep learning.

Then I ran the same query for 2023-2026, to see how dominant LLMs were. 59% of the top 100 upvoted papers were about LLMs or AI.

So I asked him to make a nice chart with all of this:

Then I wanted to see which 2019 papers aged well, so I asked Claude to pull the ones that held up from the top 100. Here’s what he got:

MuZero — Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model (161 pts) — DeepMind’s successor to AlphaZero
EfficientNet — Rethinking Model Scaling for Convolutional Neural Networks (119 pts) — compound scaling, set the new CV SOTA
XLNet — Generalized Autoregressive Pretraining for Language Understanding (79 pts) — briefly dethroned BERT
PyTorch: An Imperative Style, High-Performance Deep Learning Library (113 pts) — the NeurIPS paper formalizing PyTorch’s design
On the Measure of Intelligence (80 pts) — Chollet’s ARC / “human-like intelligence” manifesto

It’s too early to know which 2023-2026 papers will hold up, so I asked Claude to guess:

DeepSeek-R1 — Incentivizing Reasoning Capability in LLMs via RL (1,351 pts) — first open recipe for o1-style reasoning via pure RL on verifiable rewards
Generative Agents — Interactive Simulacra of Human Behavior (391 pts) — the canonical “Smallville” paper, template for LLM agent architectures
The Era of 1-bit LLMs — BitNet b1.58, ternary parameters for cost-effective computing (1,040 pts) — first credible case for low-bit inference as the default
Differential Transformer (562 pts) — attention with a noise-cancelling term, clean architectural contribution with a real theoretical story
LK-99 cluster — room-temperature superconductor preprints (2,408 + 1,690 pts) — landmark meta-science, not physics: open-science-at-wire-speed and the canonical case of crowdsourced replication

That was fun. Thanks, Claude.

BibTeX citation:

@online{castillo2026,
  author = {Castillo, Dylan},
  title = {LLM Research on {Hacker} {News} Is Drying Up},
  date = {2026-04-24},
  url = {https://dylancastillo.co/til/llm-research-on-hacker-news-is-dying.html},
  langid = {en}
}

关于 Hacker News 的 LLM 研究正在减少。 LLM research on Hacker News is drying up

关于 Hacker News 的 LLM 研究正在减少。
LLM research on Hacker News is drying up